skills/tiangong-ai/skills/github-contribution-period-analysis

github-contribution-period-analysis

SKILL.md

GitHub Contribution Period Analysis

Core Goal

  • Build an evidence-based Markdown report for one target GitHub user in a UTC time window.
  • Focus on practical code contribution signals: merged PR and commit activity.
  • Cover both own repositories and other repositories, limited by credential access.

Workflow

  1. Prepare authentication for GitHub API access.
  2. Run scripts/github_contribution_report.py with target user and time window.
  3. Review the generated Markdown report and inspect evidence links.

Command

python3 scripts/github_contribution_report.py \
  --user <github-login> \
  --start 2026-03-01 \
  --end 2026-03-08 \
  --output /tmp/github-contribution-report.md

Output Semantics

  • Included contribution types:
    • Authored merged PRs.
    • PRs merged by the target user (maintainer merge work).
    • Authored commits.
  • Excluded activity types:
    • Comments, reviews, stars, watches, forks.
  • The report contains:
    • Scope and coverage notes.
    • Summary metrics.
    • Substantive work categories inferred from PR/commit evidence.
    • Work content highlights with representative evidence links.
    • Repository breakdown.
    • Per-repository concrete change details (for every changed repository).
    • Contribution timeline.
    • Top contribution tables.
    • Evidence appendix with PR/commit URLs.

Important Constraints

  • SSH key alone is for git transport and does not directly authorize GitHub REST API calls.
  • Private repository coverage needs authenticated API access, typically via GITHUB_TOKEN/GH_TOKEN or gh auth token.
  • GitHub Search API has a 1000-item cap per query. For very active users, split the time range and run multiple reports.

References

  • references/env.md
  • references/data-model.md
  • references/markdown-template.md

Scripts

  • scripts/github_contribution_report.py
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